Dr. Dong Yang Profile

Dr. Dong Yang

at Carestream Health Inc

SPIE Involvement:

Author

Publications (16)

Proceedings Article | 15 March 2019 Presentation + Paper

Coupled active shape models for automated segmentation and landmark localization in high-resolution CT of the foot and ankle

M. Brehler, A. Islam, L. Vogelsang, D. Yang, W. Sehnert, D. Shakoor, S. Demehri, J. Siewerdsen, W. Zbijewski

Proc. SPIE. 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Data modeling, Image segmentation, Diagnostics, 3D modeling, Bone, Shape analysis, Biomedical engineering, 3D image processing

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Purpose: We develop an Active Shape Model (ASM) framework for automated bone segmentation and anatomical landmark localization in weight-bearing Cone-Beam CT (CBCT). To achieve a robust shape model fit in narrow joint spaces of the foot (0.5 – 1 mm), a new approach for incorporating proximity constraints in ASM (coupled ASM, cASM) is proposed. Methods: In cASM, shape models of multiple adjacent foot bones are jointly fit to the CBCT volume. This coupling enables checking for proximity between the evolving shapes to avoid situations where a conventional single-bone ASM might erroneously fit to articular surfaces of neighbouring bones. We used 21 extremity CBCT scans of the weight-bearing foot to compare segmentation and landmark localization accuracy of ASM and cASM in leave-one-out validation. Each scan was used as a test image once; shape models of calcaneus, talus, navicular, and cuboid were built from manual surface segmentations of the remaining 20 scans. The models were augmented with seven anatomical landmarks used for common measurements of foot alignment. The landmarks were identified in the original CBCT volumes and mapped onto mean bone shape surfaces. ASM and cASM were run for 100 iterations, and the number of principal shape components was increased every 10 iterations. Automated landmark localization was achieved by applying known point correspondences between landmark vertices on the mean shape and vertices of the final active shape segmentation of the test image. Results: Root Mean Squared (RMS) error of bone surface segmentation improved from 3.6 mm with conventional ASM to 2.7 mm with cASM. Furthermore, cASM achieved convergence (no change in RMS error with iteration) after ~40 iterations of shape fitting, compared to ~60 iterations for ASM. Distance error in landmark localization was 25% to 55% lower (depending on the landmark) with cASM than with ASM. The importance of using a coupled model is underscored by the finding that cASM detected and corrected collisions between evolving shapes in 50% to 80% (depending on the bone) of shape model fits. Conclusion: The proposed cASM framework improves accuracy of shape model fits, especially in complexes of tightly interlocking, articulated joints. The approach enables automated anatomical analysis in volumetric imaging of the foot and ankle, where narrow joint spaces challenge conventional shape models.

Proceedings Article | 19 March 2014 Paper

High-performance soft-tissue imaging in extremity cone-beam CT

W. Zbijewski, A. Sisniega, J. Stayman, A. Muhit, G. Thawait, N. Packard, R. Senn, D. Yang, J. Yorkston, J. Carrino, J. Siewerdsen

Proc. SPIE. 9033, Medical Imaging 2014: Physics of Medical Imaging

KEYWORDS: Visualization, Imaging systems, Sensors, Denoising, Photons, Computer simulations, Bone, Monte Carlo methods, Image quality, Computed tomography

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Proceedings Article | 29 March 2013 Paper

Peripheral quantitative CT (pQCT) using a dedicated extremity cone-beam CT scanner

A. Muhit, S. Arora, M. Ogawa, Y. Ding, W. Zbijewski, J. Stayman, G. Thawait, N. Packard, R. Senn, D. Yang, J. Yorkston, C. Bingham, K. Means, J. Carrino, J. Siewerdsen

Proc. SPIE. 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Minerals, X-ray computed tomography, Imaging systems, Calibration, Scanners, Ions, Bone, Computed tomography, Spatial resolution, Neodymium

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Purpose: We describe the initial assessment of the peripheral quantitative CT (pQCT) imaging capabilities of a conebeam CT (CBCT) scanner dedicated to musculoskeletal extremity imaging. The aim is to accurately measure and quantify bone and joint morphology using information automatically acquired with each CBCT scan, thereby reducing the need for a separate pQCT exam. Methods: A prototype CBCT scanner providing isotropic, sub-millimeter spatial resolution and soft-tissue contrast resolution comparable or superior to standard multi-detector CT (MDCT) has been developed for extremity imaging, including the capability for weight-bearing exams and multi-mode (radiography, fluoroscopy, and volumetric) imaging. Assessment of pQCT performance included measurement of bone mineral density (BMD), morphometric parameters of subchondral bone architecture, and joint space analysis. Measurements employed phantoms, cadavers, and patients from an ongoing pilot study imaged with the CBCT prototype (at various acquisition, calibration, and reconstruction techniques) in comparison to MDCT (using pQCT protocols for analysis of BMD) and micro-CT (for analysis of subchondral morphometry). Results: The CBCT extremity scanner yielded BMD measurement within ±2-3% error in both phantom studies and cadaver extremity specimens. Subchondral bone architecture (bone volume fraction, trabecular thickness, degree of anisotropy, and structure model index) exhibited good correlation with gold standard micro-CT (error ~5%), surpassing the conventional limitations of spatial resolution in clinical MDCT scanners. Joint space analysis demonstrated the potential for sensitive 3D joint space mapping beyond that of qualitative radiographic scores in application to non-weight-bearing versus weight-bearing lower extremities and assessment of phalangeal joint space integrity in the upper extremities. Conclusion: The CBCT extremity scanner demonstrated promising initial results in accurate pQCT analysis from images acquired with each CBCT scan. Future studies will include improved x-ray scatter correction and image reconstruction techniques to further improve accuracy and to correlate pQCT metrics with known pathology.

Proceedings Article | 6 March 2013 Paper

Physical model-based metal artifact reduction (MAR) scheme for a 3D cone-beam CT extremity imaging system

D. Yang, R. Senn, N. Packard, S. Richard, J. Yorkston

Proc. SPIE. 8668, Medical Imaging 2013: Physics of Medical Imaging

KEYWORDS: X-ray computed tomography, CT reconstruction, Imaging systems, Sensors, Metals, Image segmentation, X-rays, 3D modeling, Signal processing, Reconstruction algorithms

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Proceedings Article | 3 March 2012 Paper

Dose and scatter characteristics of a novel cone beam CT system for musculoskeletal extremities

W. Zbijewski, A. Sisniega, J. Vaquero, A. Muhit, N. Packard, R. Senn, D. Yang, J. Yorkston, J. Carrino, J. Siewerdsen

Proc. SPIE. 8313, Medical Imaging 2012: Physics of Medical Imaging

KEYWORDS: X-ray computed tomography, Imaging systems, Sensors, Scanners, X-rays, Computer simulations, Bone, Monte Carlo methods, Systems modeling, Prototyping

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A novel cone-beam CT (CBCT) system has been developed with promising capabilities for musculoskeletal imaging (e.g., weight-bearing extremities and combined radiographic / volumetric imaging). The prototype system demonstrates diagnostic-quality imaging performance, while the compact geometry and short scan orbit raise new considerations for scatter management and dose characterization that challenge conventional methods. The compact geometry leads to elevated, heterogeneous x-ray scatter distributions - even for small anatomical sites (e.g., knee or wrist), and the short scan orbit results in a non-uniform dose distribution. These complex dose and scatter distributions were investigated via experimental measurements and GPU-accelerated Monte Carlo (MC) simulation. The combination provided a powerful basis for characterizing dose distributions in patient-specific anatomy, investigating the benefits of an antiscatter grid, and examining distinct contributions of coherent and incoherent scatter in artifact correction. Measurements with a 16 cm CTDI phantom show that the dose from the short-scan orbit (0.09 mGy/mAs at isocenter) varies from 0.16 to 0.05 mGy/mAs at various locations on the periphery (all obtained at 80 kVp). MC estimation agreed with dose measurements within 10-15%. Dose distribution in patient-specific anatomy was computed with MC, confirming such heterogeneity and highlighting the elevated energy deposition in bone (factor of ~5-10) compared to soft-tissue. Scatter-to-primary ratio (SPR) up to ~1.5-2 was evident in some regions of the knee. A 10:1 antiscatter grid was found earlier to result in significant improvement in soft-tissue imaging performance without increase in dose. The results of MC simulations elucidated the mechanism behind scatter reduction in the presence of a grid. A ~3-fold reduction in average SPR was found in the MC simulations; however, a linear grid was found to impart additional heterogeneity in the scatter distribution, mainly due to the increase in the contribution of coherent scatter with increased spatial variation. Scatter correction using MC-generated scatter distributions demonstrated significant improvement in cupping and streaks. Physical experimentation combined with GPU-accelerated MC simulation provided a sophisticated, yet practical approach in identifying low-dose acquisition techniques, optimizing scatter correction methods, and evaluating patientspecific dose.

Proceedings Article | 24 February 2012 Paper

Image quality improvement through fusion of hybrid bone- and soft-tissue-texture filtering for 3D cone beam CT extremity imaging system

D. Yang, R. Senn, N. Packard, J. Yorkston, D. Foos

Proc. SPIE. 8314, Medical Imaging 2012: Image Processing

KEYWORDS: X-ray computed tomography, Tissues, Imaging systems, Denoising, X-rays, Linear filtering, Bone, Image quality, Image filtering, 3D image processing

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Proceedings Article | 16 March 2011 Paper

Design and optimization of a dedicated cone-beam CT system for musculoskeletal extremities imaging

W. Zbijewski, P. De Jean, P. Prakash, Y. Ding, J. Stayman, N. Packard, R. Senn, D. Yang, J. Yorkston, A. Machado, J. Carrino, J. Siewerdsen

Proc. SPIE. 7961, Medical Imaging 2011: Physics of Medical Imaging

KEYWORDS: X-ray computed tomography, Imaging systems, Sensors, Scanners, X-rays, Copper, Interference (communication), 3D modeling, Bone, Signal detection

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Proceedings Article | 27 March 2009 Paper

Image quality improvement based on wavelet regularization for cone beam breast CT (CBBCT)

Dong Yang, Ruola Ning, Xiaohua Zhang, Ricardo Betancourt, Shaohua Liu

Proc. SPIE. 7259, Medical Imaging 2009: Image Processing

KEYWORDS: Signal to noise ratio, Breast, Wavelets, X-rays, Interference (communication), Linear filtering, Image filtering, Reconstruction algorithms, Modulation transfer functions, Spatial resolution

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Proceedings Article | 3 March 2009 Paper

Three dimensional breast masses autodetection in cone beam breast CT

Xiaohua Zhang, Ruola Ning, Dong Yang

Proc. SPIE. 7260, Medical Imaging 2009: Computer-Aided Diagnosis

KEYWORDS: Breast, Tumors, Tissues, Digital filtering, Iris recognition, Image filtering, Mammography, Computed tomography, Computer aided design, 3D image processing

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Proceedings Article | 3 April 2008 Paper

Cone beam CT tumor vasculature dynamic study (Murine model)

Dong Yang, Ruola Ning, David Conover, Betancourt Ricardo, Shaohua Liu

Proc. SPIE. 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images

KEYWORDS: Breast, X-ray computed tomography, Tumors, Sensors, Blood vessels, Magnetic resonance imaging, Image segmentation, X-rays, Spatial resolution, 3D image processing

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Proceedings Article | 16 March 2007 Paper

Implementation and evaluation of 4D cone beam CT (CBCT) reconstruction

Dong Yang, Ruola Ning, Shaohua Liu, David Conover

Proc. SPIE. 6510, Medical Imaging 2007: Physics of Medical Imaging

KEYWORDS: X-ray computed tomography, Tumors, Sensors, Signal attenuation, Blood vessels, X-rays, Computer simulations, Solids, 3D metrology, Prototyping

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Proceedings Article | 2 March 2006 Paper

Flat panel detector-based cone beam CT for dynamic imaging: system evaluation

Ruola Ning, David Conover, Yong Yu, Yan Zhang, Weixing Cai, Dong Yang, Xianghua Lu

Proc. SPIE. 6142, Medical Imaging 2006: Physics of Medical Imaging

KEYWORDS: Breast, Chest, X-ray computed tomography, Imaging systems, Sensors, X-rays, Data acquisition, X-ray imaging, X-ray detectors, Prototyping

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Proceedings Article | 2 March 2006 Paper

Computer simulation of FDK reconstruction with the in-line holographic projection data

Weixing Cai, Ruola Ning, Dong Yang

Proc. SPIE. 6142, Medical Imaging 2006: Physics of Medical Imaging

KEYWORDS: Holography, Phase contrast, 3D image reconstruction, Detection and tracking algorithms, Sensors, Signal attenuation, X-rays, X-ray sources, Computer simulations, Reconstruction algorithms

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Proceedings Article | 2 March 2006 Paper

Reconstruction implementation based on a flat panel detector cone beam breast CT

Dong Yang, Ruola Ning, David Conover, Yong Yu

Proc. SPIE. 6142, Medical Imaging 2006: Physics of Medical Imaging

KEYWORDS: Breast, Radon, X-ray computed tomography, Sensors, X-rays, Computer simulations, Mammography, Reconstruction algorithms, X-ray imaging, 3D image processing

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Proceedings Article | 20 April 2005 Paper

Modified FDK half-scan (MFDKHS) scheme on flat panel detector-based cone-beam CT

Dong Yang, Ruola Ning, Yong Yu, David Conover, Xianghua Lu

Proc. SPIE. 5745, Medical Imaging 2005: Physics of Medical Imaging

KEYWORDS: Radon, Fluctuations and noise, 3D image reconstruction, Detection and tracking algorithms, Sensors, Signal attenuation, Temporal resolution, Reconstruction algorithms, Algorithm development, Breast imaging

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Proceedings Article | 6 May 2004 Paper

Implementation and evaluation of the half-scan scheme based on CBCT (cone-beam CT) system

Dong Yang, Ruola Ning, Yong Yu, David Conover, Xianghua Lu

Proc. SPIE. 5368, Medical Imaging 2004: Physics of Medical Imaging

KEYWORDS: Breast, X-ray computed tomography, Detection and tracking algorithms, Tumors, Sensors, X-rays, Temporal resolution, Reconstruction algorithms, Prototyping, Breast imaging

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Showing 5 of 16 publications

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